Instructions to use merve/hyperparam_table with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Keras
How to use merve/hyperparam_table with Keras:
# Available backend options are: "jax", "torch", "tensorflow". import os os.environ["KERAS_BACKEND"] = "jax" import keras model = keras.saving.load_model("hf://merve/hyperparam_table") - Notebooks
- Google Colab
- Kaggle

- Xet hash:
- d2860d648d51f5eb6a22c9d6c21d22e81f7c4dfdd2c21e4e5fb10ca907e383f9
- Size of remote file:
- 5.22 kB
- SHA256:
- d1f56ced305afc4288651955543cd447015ffdb17fbfda2e69c3f5565e6725cb
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